Answering questions about an image using outside knowledge
Answering questions about an image using outside knowledge
KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA
arXiv paper abstract https://arxiv.org/abs/2012.11014
arXiv PDF paper https://arxiv.org/pdf/2012.11014.pdf
Facebook Research https://research.fb.com/publications/krisp-integrating-implicit-and-symbolic-knowledge-for-open-domain-knowledge-based-vqa/
One of the most challenging question types in VQA is when answering the question requires outside knowledge not present in the image.
... We tap into two types of knowledge representations and reasoning.
First, implicit knowledge which can be learned effectively from unsupervised language pre-training and supervised training ...
Second, explicit, symbolic knowledge encoded in knowledge bases.
... We combine diverse sources of knowledge to cover the wide variety of knowledge needed to solve knowledge-based questions.
... KRISP (Knowledge Reasoning with Implicit and Symbolic rePresentations), significantly outperforms state-of-the-art on OK-VQA, the largest available dataset for open-domain knowledge-based VQA. ...
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